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Neurophysiology of intra-and inter-species emotional interactions. Personality trait effect, P300 and N300 ERPs measures

Authors:
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: http://dx.doi.org/10.7358/neur-2018-023-bal2
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Neurophysiology of intra- and
inter-species emotional interactions.
Personality trait effect, P300 and
N300 ERPs measures
Michela Balconi1,2 - Davide Crivelli1,2 - Maria Elide Vanutelli1,2,3
1 Department of Psychology, Catholic University of the Sacred Heart, Milan, Italy
2
Research Unit in Affective and Social Neuroscience, Catholic University of the Sacred Heart, Milan, Italy
3 Department of Philosophy, University of Milan, Milan, Italy
michela.balconi@unicatt.it
ABSTRACT
Emotional empathy plays a crucial role in
social intra-species and inter-species
interactions. However the role of interspecies interactio
ns and of some personality
components was underestimated. The presen
t research explored electrophysiological
correlates of affective processing in rela
tion to emotionally valenced human-human
(HH) and human-animal (HA) interactions.
Further, we explored the link between
such cortical responses and personality empa
thic profile as measured by the Balanced
Emotional Empathy Scale (BEES) and the Interpersonal Reactivity Index (IRI). Both
HH and HA interactions was associated to a significant increase
of N300 and P300
deflections in response to positive and ne
gative compared with neutral interactions.
However, whereas N300 was mainly influenc
ed by stimuli valence and was frontally
distributed, P300 seemed to be mainly modulated by the stimuli
attentional relevance
and showed even a posterior distribution.
Finally, a significant association was found
between emotional empathy trait (BEES) and
N300 amplitude. Results are discussed in
light of the significance of empathic traits in mediating species-specific and species-
aspecific relationships.
Keywords: Emotional empathy; intra/inter-species; BEES; IRI; N300/P300
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1. INTRODUCTION
Emotional responsiveness plays a fundam
ental role in interpersonal behaviour
and comprehending the processes underlying such skill is crucial to understand
why and how we engage in social interactions (Westbury & Neumann, 2008).
The ability to adopt other people’s pers
pective, monitoring and self-regulatory
mechanisms that keep track of the or
igins of our own and others’ emotions,
and the ability to affectively respond to
others’ emotional state which often
entails the capacity to share this state (Balconi, Bortolotti, & Gonzaga, 2011;
Preston & de Waal, 2002) – are basic components of the behavioural response
to interpersonal situations. In this light, empathy and personality trait
components seem related to the ability to understand others’ emotions and
feelings, with “resonance” mechanisms that mediate a direct form of
understanding between the observer and the observed person (Balconi &
Bortolotti, 2014; Balconi & Canavesio,
2014). An interesting approach rooted
in ethology and evolutionary neurosci
ence was proposed by Preston and de
Waal (Preston & de Waal, 2002), that is
the Perception-Action Model (PAM).
According to the PAM, the observation of another’s emotional states
automatically and unconsciously triggers corresponding neural representations
in the observer. Importantly, the more similar and close two individuals are, the
easier the tuning (de Waal, 2008). Addi
tionally, the PAM outlines some other
factors that could mediate emotional sharing and empathic mechanisms. In
studies involving humans, several factors that can increase the perception of
closeness and similarity, and consequently emotional understanding, have been
investigated, with cultural similarity, se
ntience or social circumstance being the
most influential (Westbury & Neuma
nn, 2008). Nonetheless, while those
affective mechanisms and their underl
ying cortical networks have been
explored in the last years in human contexts (Balconi, Bortolotti, & Crivelli,
2012; Balconi & Canavesio, 2013b; Decety & Grèzes, 2006; Gallese, 2003),
limited research focused on non-human social relationships (Balconi &
Vanutelli, 2016). In the present study the role of different contexts in
influencing affective tuning has been co
mpared with respect to intra-species and
inter-species relationships. In
deed, it is still not clear to which extent humans are
able to present emotional and emphatic responses with respect to conspecifics
involved in human-animal interaction scen
es representing positive or negative
exchanges. In fact, according to the biological significance of this kind of
relationship, there is a need to improv
e our knowledge about the nature and the
cortical correlates of human emotional behaviour in response to inter-species
affective interactions where humans and animals are represented together.
Indeed, only a few studies focused on humans’ emotional response to
different species (Westbury & Neumann, 2008) or to humans’ behaviour
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observing specific situations where an
imals are implicated (such as pain
perception) (Franklin et al., 2013), without a specific attention on the
emotional significance and valence of the
interactions between different species.
Therefore, the significance that inter-species relationships may have in
processing emotions is unexplored. Thus
, with the present research, we aimed
at examining the brain contribution to emotional behaviour in response to
interactive situations including humans (HH) or humans and animals (HA)
taking into account the specific role of co
rtical structures in processing different
emotionally valenced species-specific an
d species-aspecific interactions. Such
additional focus on interactions between different species may shed light on the
hypothesis concerning the homogeneity of the emotional behaviour and of the
emotional brain response even to inter-species interactional contexts. According
to previous results, we think that the ability to respond to emotionally
connoted interpersonal situations may be modulated by prefrontal functioning,
since this cortical area could act as a regulator and “mediator” of emotional
mechanisms (Balconi et al., 2011; Balconi & Bortolotti, 2012a, 2012b, 2012c;
Balconi & Caldiroli, 2011; Balconi, Falbo, & Conte, 2012; Rameson &
Lieberman, 2009). In other words, this cortical activity may have a direct
influence in modulating subjects’ responsiveness to the interpersonal situations,
independently from HH and HA conditions.
Secondly a direct comparison between emotion-related positive and
negative patterns was considered. To explore these points, to investigate neural
correlates underlying reactions to e
mpathic-behaviours, and to study the
relation between cortical responses and interpersonal context, we applied event-
related potentials analysis (ERPs). Two ERP deflections were specifically
analyzed, i.e. the P300 and N300 components. These deflections were deemed
as specific markers of the emotional valu
e, the relevance and the salience of a
situation, as well as of the emotiona
l involvement (arousal) of the subject
(Balconi & Caldiroli, 2011). Indeed, as for the first positive deflection,
Cuthbert and colleagues (Cuthbert, Schupp, Bradley, Birbaumer, & Lang,
2000) suggested that P300 can be evoked during picture viewing and
augmented for emotional laden stimuli, mirroring an increase in resource
allocation to motivationally relevant cues. Affective stimuli capture attention
and receive increased resources, which fa
cilitate their processing compared to
neutral material, and such facilitation seems to relate to the modulation in the
P300 (Rossignol, Philippot, Douilliez, Crommelinck, & Campanella, 2005).
Enhanced late positive going waveforms ha
ve indeed been observed in response
to the presentation of pleasant and unpleasant pictures from the International
Affective Picture System (IAPS) (Cuthb
ert et al., 2000; Schupp et al., 2000;
Schutter, De Haan, & Van Honk, 2004). It was also shown that the P300 is
often modulated by the arousing content and cognitive engagement of stimuli
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(Ruz, Madrid, & Tudela, 2013). Moreover several previous stud
ies reported that
P300 amplitude depends on the subjective
relevance of information conveyed by
the stimulus, including its emotional connotation (Amrhein, Mühlberger, Pauli,
& Wiedemann, 2004; Conroy & Polich
, 2007; Delplanque, Silvert, Hot, &
Sequeira, 2005; Palomba, Angrilli, & Mini, 1997). Thus, for example
Delplanque and colleagues (2005) report
ed an increase in P300 amplitude for
pleasant and unpleasant novel stimuli relative to neutra
l novel ones, which
suggests that attentional processes indexed
by P300 are influenced by the affective
valence and arousal features of a stimul
us. Therefore we may suppose that this
positive deflection subserve
s a specific emotion-related neural mechanism, which
mirrors the salience and the attentional demand for the processed stimuli more
than their specific hedonic valence.
As for the second deflection, the N300 component has been linked to the
affective evaluation of stimuli (Carreti
é & Iglesias, 1995; Rossignol, Philippot,
Douilliez, Crommelinck, & Campanella, 2005), and it is supposed to mirror
the depth of emotional processing or the affective significance of the stimulus.
According to Halgren and Marinkovich (Halgren & Marinkovich, 1994) the
initial non-discriminatory step of the emotional reaction – the so called
orienting complex (reflected in N200; Näätänen & Gaillard, 1983) – is
succeeded by the ‘emotional event integrat
ion’ step, which is influenced by the
emotional connotation of the stimuli. Th
is second step is indeed associated,
among other mechanisms, to the integration of the perceived emotional
stimulus and the models filed in long-t
erm memory. Moreover, in relation to
stimulus valence, several studies indicate
that negative events elicit more rapid
and more prominent responses than neutra
l or positive events. This ‘negativity
bias’ is manifested through different re
sponse systems, including those related
to cognitive, emotional, and social
behaviour (Balconi & Mazza, 2009;
Cacioppo & Gardner, 1999; Carretié,
Mercado, Tapia, & Hinojosa, 2001).
Therefore, we expected significantly increased P300/N300 amplitudes in
response to interpersonal negative
and menacing interactions. Greater
P300/N300 deflections were also expected
for HA negative situations, since a
potential increase in attentional relevance is likely induced by depicted threats.
Thirdly, the direct relation between cortical responses to emotional
contexts and personality profiles and, sp
ecifically, ERPs modulations in relation
to the empathic attitude shown by the pa
rticipants. Empathy-related traits were
measured by the BEES scale (Balance Emotional Empathy Scale; Mehrabian &
Epstein, 1972). In the context of pe
rsonality measurement, it describes
individual differences in the tendency to show emotional empathy towards
others. In addition, BEES has been found to reflect interpersonal attitudes. The
Interpersonal Reactivity Index (IRI; Davis,
1980) was also administered to test
the multidimensional aspects of empathic behaviour and the cognitive
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component of empathy. IRI taps on four separate aspects of empathy and its
relations to social functioning measures, self-esteem, emotionality, and
sensitivity to others. Each of the four subscales displays a distinctive and
predictable pattern of relations with th
ose measures, as well as with previous
unidimensional empathy measures. We su
pposed that those effects would have
been accentuated in high empathic tr
ait participants with respect to low
empathic trait ones in case of both HH and HA interactions.
2. MATERIALS AND METHODS
2.1 Subjects
16 subjects, 8 females and 8 males (Mage
= 26.17; SD = 2.20; range = 23-33) took
part in the experiment All subjects were right-handed, with normal or corrected-
to-normal visual acuity. Exclusion crit
eria were neurological or psychiatric
pathologies. They gave informed written consent for participating in the study
and the research was approved by the ethical committee of the institution
(Department of Psychology, Catholic University of Milan) where the work was
carried out. The experiment was conducted in accordance wi
th the Declaration
of Helsinki and all the procedure was carr
ied out with adequate understanding of
the subjects, who read and signed the Research Consent Form before
participating in this research. No paym
ent was provided for their performance.
One female participant was not included
in the final set of analyses (N = 15)
because of EEG artifacts. No other participants or data were excluded from
analyses and we report evidences concerning all manipulations in the study.
2.2 Stimuli
Subjects were presented with affective pictures depicting human-human (HH) and
human-animal (HA) interactions. The stimuli set was constituted by 48 coloured
realistic images representing positive, negative and neutral interaction between
humans (24 pictures) and humans and animals (24 pictures). Pictures were equally
divided with respect to emotional valence (positive, negative and neutral scenes).
Positive pictures represented positive and cooperative interactions between HH or
HA. Negative pictures represented negative and uncooperative interactions between
HH and HA, Neutral pictures represented interactions without a specific valence
between HH and HA (Figure 1
). All pictures had the same size (14 cm x 10 cm)
and they were similar for perceptual features such as luminance, as measured with a
photometer, and complexity (i.e. number of
details in the scene as assessed by six
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judges in the validation phase, see ahea
d). No significant effects emerged with
respect to species or valence. Scenes were
also completely balanced with respect to
actors’ gender and animals’ species (dogs and cats).
Stimuli were selected according to pre-
experimental validation scores. Each
scene was evaluated by six judges with respect to valence and arousal dimensions,
using the Self-Assessment Manikin Scale with a five-point Likert Scale (Bradley
& Lang, 1994, 2007). Also, they were asked to rate pictures
for complexity.
Ratings were averaged across all presented pictures for each condition. For what
concerns SAM ratings the statistical analysis (ANOVA) showed that they differed
in term of valence (more posi
tive for positive pictures than the other pictures for
HH and HA; more negative for negative pictures than the other pictures for HH
and HA; with intermediate values for neut
ral pictures than the other pictures for
HH and HA; all significant contrast comparisons: P
.05) and arousal (more
arousing for positive and negative pictures than neutral pict
ures for HH and HA;
P
.05). For what concerns complexity, no significant differences emerged with
respect to the different conditions (P ≥ .05).
Figure 1. Some examples of emotional interaction scene
s. Top: HH pictures; from left to
right: positive, negative, neutral stimuli. Bottom: HA pictures; from left to right:
positive, negative, neutral stimuli
2.3 Procedure
Subjects were seated in a dimly lit r
oom, facing a computer monitor (distance:
70 cm). Stimuli were presented using E-Prime 2.0 software (Psychology
Software Tools Inc., Sharpsburg, PA,
USA) running on a personal computer
with a 15-inch screen. Participants were
asked to observe each stimulus during
EEG measure recording, and to attend to the images for the entire time of
exposure. Moreover, they were asked to try to enter into the other persons’
situation (“
try to empathize with the people represented entering in his/her
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feelings
”). In order to facilitate empathic resonance with the reproduced scene,
actors were similar in age to the experimental participants. A specific
questionnaire was used in order to assess
the subjects’ self-rating on key aspects
of subjective evaluation to the empathic task. The questionnaire was used in a
post-experiment section. The aspects ex
amined included degree of experienced
empathy (“How much did you enter into the actor’s feelings and situations
?”),
personal emotional involvement (“
How much did you feel emotionally involved
in the situation?”), semantic attribution of the
situation (positive, negative and
neutral) (“How do you classify the interpersonal situation?”
, emotional
significance (high or low) (“
Did you perceive an emotional significance (response
by the participants) of the situation?”)
. All subjects experienced a high sense of
empathy, they were emotionally engaged
in the task and they were able to
attribute a coherent emotional value to the pictures.
Pictures were randomly presented at the centre of the computer monitor
for 6 seconds, with an inter-stimulus interval of 8 seconds. Each picture was
presented for three times (24 stimuli for each category), for a total of 72
presentations for both the HH and the HA condition.
120 seconds resting baseline was recorded at the beginning of the
experiment. After the experimental phase,
subjects were asked to rate pictures
hedonic valence and arousal dimensions on the SAM scale (five-points version).
As shown by statistical analysis (rep
eated measures ANOVA with independent
factor valence, 3, x condition, 2 HH vs. HA) pictures differed in terms of
valence (all paired comparisons P ≤ .05; for positive HH: M = 4.31, SD
= .03;
HA: M = 4.23, SD = .04; negative HH: M = 2.07, SD = .02; HA: M
= 1.97,
SD = .03; neutral HH: M = 3.08, SD = .04; HA: M = 3.32, SD
= .03) and
arousal (for the positive HH: M = 3.24, SD = .02; HA: M = 4.04, SD
= .03;
negative HH: M = 3.22, SD = .28; HA: M = 3.57, SD = .29; neutral HH: M
=
2.28, SD = .04; HA: M = 2.38, SD
= .02; with significant differences only for
neutral vs. positive and neutral vs. negative scenes for both HH and HA, P
.05). Finally subjects were asked to
complete the BEES and IRI questionnaire
(see Figure. 2).
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Figure 2. Experimental design and EEG recording steps
2.4 BEES Measure
Trait empathy was assessed by the BEES
questionnaire (Mehrabian & Epstein,
1972). It consists of 30 items, structured as Likert scales ranging from -4 (
very
strong disagreement) to +4 (very strong agreement
). Higher scores represent higher
levels of emotional empathy. The sample mean score was equal to 40.62 (SD
=
5.98, range = -4 81). Inter-item Cronbach’s alpha was calculated for BEES
data (total 0.88).
2.5 IRI measure
The Interpersonal Reactivity Index (IRI) is
a questionnaire used to measure both
cognitive and emotional components of empathy. It consists of 28 items, each including
a 5-point Likert scale ranging from It does not describe me well” to
It describes me very
well
”. The questionnaire has 4 subscales constituted by seven different items each:
Perspective Taking; Fantasy; Empathic Concern; Personal Distress
(Davis, 1983). The
sample mean score was equal to 61.22 (SD
= 7.39, range = 58-93). We used the Italian
validated version of the questionnaire (Albiero, Ingoglia, & Lo Coco, 2006).
2.6 EEG recording and data reduction
A 16-channel portable EEG system (V-Amp
, Brain Products GmbH, Gilching,
Germany) was used for data acquisition.
An EEG cap with Ag/AgCl electrodes
was used to record EEG from active scalp sites referred to ea
rlobes (10-5 system
of electrode placement). EEG activity was recorded from the following
positions: AFF3, AFF4, Fz, AFp1, AFp2, C3, C4, Cz, P3, P4, Pz, T7, T8, O1,
O2. The cap was fixed with a chin strap to prevent movement during the task.
Data were sampled at 1000 Hz, with a ba
ndpass input filter set from 0.01 Hz
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to 100 Hz and with a 50 Hz notch filter. The impedance of recording
electrodes was monitored for each subject prior to data collection and it was
always kept below 5 k
. Additionally, EOG electrodes were sited on the outer
canthi to detect blinks and eye movements for subsequent ocular artifacts
correction. After offline filtering through a 0.1-30 Hz bandpass filter, data were
corrected by an ICA-based algorithm (Jung et al., 2000) and a computerized
artifact rejection criterion excluded tr
ials when the peak-to-peak amplitude
exceeded 40 μV. The signal was then visually
checked to reject all residual
ocular, muscular, or movement artifacts and to increase specificity. After
performing EOG correction and visual inspection, only artifact-free trials were
considered (rejected epochs, 3%). An averaged waveform (off-line) was
obtained for each condition (not less than 20 epochs per condition entered the
computation). The peak amplitude (from the baseline) was quantified relative to
the 150 ms pre-stimulus window by identi
fying the most negative and positive
peaks within the temporal window from
230 to 400 ms post-stimulus. The onset
was coincident with the appearance of th
e stimulus on the screen. Morphological
analysis of the EEG profile confirmed th
at the peak deflections were included
within those time ranges. Peak amplitude and latency data were extracted
respectively for P300 and N
300 components, and distinct analyses were applied
to each of the average profiles. Subsequent
ly, localization (three sites: frontal,
AFF3/AFF4 and AFp1/AFp2; temporo-cen
tral, C3/C4 and T7/T8 and parietal,
P3/P4) and lateralization (two sides: left and right electrode positions) factors
were explored by focused statistical analyses. Preliminary tests did not highlight
significant latency differences across cond
itions. We then did not include this
measure within the final set of analyses. The mean latency of the two
components was approximately 360 ms and 300 ms.
3. RESULTS
A set of analyses was performed on the data. A first set of ANOVAs was applied
to the peak amplitude of N300 and P3
00 ERP. A second set of correlation
analyses was applied to BEES and IRI measures and N300/P300 peak amplitude.
3.1 ANOVA
ERPs data were entered into four-ways repeated measure ANOVAs. Condition
(2, HH and HA), lateralization (2, left and right electrode sites), valence (3,
positive, negative, neutral), and localiza
tion (3, frontal, temporo-central, and
parietal sites) were included as factors of
the statistical models applied to the peak
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amplitude variable, distinctly for N300 and P300 components. Type I errors
associated with inhomogeneity of variance were controlled by decreasing the
degrees of freedom using the Greenhouse-G
eisser epsilon. Bonferroni corrections
for multiple comparisons were applied.
Post-hoc comparisons were successively
applied to the data (contrast analyses). The normal distribution of the data was
assessed by using skewness and kurtosis test in a preliminary statistical phase.
3.2 N300
As shown by ANOVA, the peak amplitude was modulated by valence (F(2,14)
=
11.50, P = 0.001,
η
2 = .44), and valence x localization (F(4,27) = 9.03, P
=
0.001,
η
2
= .40). No other main or interaction effect was statistically significant.
Post-hoc comparison revealed an increased peak amplitude for positive (F(1,14)
=
8.13, P = 0.001,
η
2 = .38) and negative (F(1,14) = 7.89, P = 0.001,
η
2
= .34) in
comparison with neutral conditions. A si
gnificant difference was also found for
negative (higher N300) compared to positive (F(1,14) = 6.58, P = 0.001,
η
2
=
.32) conditions. Moreover, the frontal
area involving AFF3, AFF4, AFp1 and
AFp2 showed a higher peak amplitude
for positive and negative conditions
compared to other cortical sites: respec
tively compared to the temporo-central
(for positive F(1,14) = 8.54, P = 0.001,
η
2 = .40; for negative F(1,14) = 9.32, P
=
0.001,
η
2 = .42); and to parietal (for positive F(1,14) = 8.23, P = 0.001,
η
2
= .40;
for negative F(1,14) = 8.04, P = 0.001,
η
2 = .39) sites.
3.3 P300
ANOVA showed significant effects for valence x localization (F(4,27)
= 11.52,
P = 0.001,
η
2 = .45) and condition x valence x localization (F(4,53) = 10.03, P
= 0.001,
η
2
= .43). No other main or interaction effect was statistically
significant. Indeed, firstly positive
and negative conditions revealed an
increased P300 amplitude than neutral conditions more localized on frontal
(for positive F(1,14) = 8.16, P = 0.001,
η
2 = .39; for negative F(1,14) = 7.78, P
= 0.001,
η
2 = .37) and parietal (for positive F(1,14) = 7.96, P = 0.001,
η
2
=
.37; for negative F(1,14) = 9.13, P = 0.001,
η
2
= .41) sites. A significant
difference was also found between HA
and HH condition, with an increased
P300 peak amplitude in HA for negative
than positive and neutral conditions
within the frontal areas over AFF3, AFF4, AFp1 and AFp2 (comparison
negative vs. positive F(1,14) = 6.73, P = 0.001,
η
2
= .34; comparison negative
vs. neutral (F(1,14) = 6.98, P = 0.001,
η
2
= .36) and parietal areas over P3 and
P4 (comparison negative vs. positive F(1,14) = 7.03, P = 0.001,
η
2
= .37;
comparison negative vs. neutral F(1,14) = 8.15, P = 0.001,
η
2 = .39).
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3.4 Correlation analyses
Pearson correlation values were appl
ied to ERPs amplitude (N300 and P300)
and BEES for HH and HA in response to positive, negative and neutral
conditions. A second set of correlations
was applied to ERPs and IRI distinctly
for HH and HA and for positive, negative and neutral conditions.
For the first set (BEES measure), as shown by statistical resu
lts, BEES scores
were significantly and positively correlated with N300
amplitude in response to
negative conditions respectively for HH (r = 0.525, P < .001) and HA (r
= 0.607
P < .001). Contrarily, no significant effect
was found for P300. As for the second
set of analyses (IRI sub-scales measures),
no statistically significant correlations
were found for both N300 and P300.
4. DISCUSSION
Empathic sensitivity to different positive
vs. negative emotional situations in
species-specific (HH) and species-aspeci
fic (HA) relationships was investigated
in the present research. This sensitivity
was tested by using psychophysiological
measures (N300 and P300 ERPs) in high
-empathic and low-empathic subjects,
according to BEES and IRI. Results confirmed the significance of emotional
empathic behaviours in response to interpersonal situations in both HH and
HA with respect to valence, while the later P300 component more highlighted
some specificities with respect to HH and HA conditions. The direct link
between these different levels of anal
ysis (i.e. ERP measures and empathic
personality traits) was discussed.
The present findings firstl
y supported the hypothesis that there is a relation
between positive (cooperative)
vs. negative (not cooperative) situations and brain
response in both HH and HA interaction types. That is, different conditions
evoked distinct ERP response patterns, with incr
eased N300 activity over
anterior frontal and frontopolar electrodes to positive
and mainly negative scenes
as compared to neutral ones in both
HH and HA interactions. The P300
component, instead, was greater over both
anterior frontal and frontopolar, but
also parietal sites (P3, P4) and showed a
more specific modulation in response to
HA scenes exclusively for negative more than positive and neutral conditions.
For what concerns N300 deflection,
the valence effect was significant
mainly with respect to negative stimul
i. Moreover, there was no distinction
between HH and HA in these reactions. This component has been linked to the
affective charge of visual stimuli (Carretié & Iglesias
, 1995; Rossignol et al.,
2005), and it is supposed to mirror the de
pth of emotional processing or the
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affective significance of the stimulus. Moreover, in relation to
stimulus valence,
several studies indicate that negative even
ts elicit more rapid and more prominent
responses than neutral or positive even
ts. This phenomenon has been called
‘negativity bias(Balconi & Mazza, 2009;
Cacioppo & Gardner, 1999; Carretié
et al., 2001). Moreover, the N300 in the anterior brain re
gion (prefrontal cortex)
has been positively associated with negati
ve valenced stimuli. In accordance with
its frontal localization, the N300 component
might be involved in the detection
and evaluation of relevant and threat
ening patterns (Posner & Raichle, 1997).
These results also suggest that the prefrontal cortex is involved in broad regulatory
control mechanisms, and again in “bringing” emotional representations online, in
maintaining, and in regulating them (Balconi & Canavesio, 2013b; Ochsner et al.,
2004). Also, the absence of relevant differences between HH and HA suggests that
this emotional modulation was not species-specific.
In contrast P300 was presumably related to attentive behaviour we adopt to
regulate our response to salient, emotional cues. This salient and potentially
dangerous situation may have determined
a higher-level attention demand: the
perception of an “uncontrolled” situation
in the case of an animal aggression may
have plausibly triggered the interactions
as highly salient and aversive. The
cortical localization of this ERP (anterior and parietal) may confirm this
attentional hypothesis, consistently
with previous research that have
demonstrated that P300 amplitude may mirror increases in
resource allocation to
motivationally relevant incentives (for a recent review see van Dinteren, Arns,
Jongsma, & Kessels, 2014). Thus, for exam
ple Delplanque and colleagues (2005)
reported an increase in P300 amplitude fo
r pleasant and unpleasant novel stimuli
relative to neutral novel ones, which sugg
ests that attentional processes indexed
by P300 are influenced by the affective va
lence and arousal features of a stimulus.
Therefore we may suppose that this positive deflection su
bserves a specific
emotion-related neural mechanism,
which mirrors the salience and the
attentional demand for the processed stim
uli more than their specific hedonic
valence. More generally, an emotion-vigilance network of attention consisting in
frontal and parietal cortices is argued to
maintain a state of alertness when salient
stimuli are encountered in high relevant
(empathic) situations. In fact, aggressive
and negative interactions are important socially aversive and potentially
threatening conditions (Balconi & Bo
rtolotti, 2012a, 2012b; Ohman, Flykt, &
Esteves, 2001), hence the involvement of the vigilance networ
k in response to
such situations can be plausibly assumed,
in particular since alertness and action
preparation are essential for appropriate responses.
Within this network, the N300 amplit
ude appeared to be significantly
modulated over the anterior brain areas
and to be valence-sensitive (Carretié,
Iglesias, & García, 1997). In contrast
, the P300 could be more directly
modulated by the level of alertness indepe
ndently from valence, on the basis of a
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Neurophysiology of intra- and inter-species emotional interactions
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mechanism for attention reso
urce allocation. The cooperative but even more
the uncooperative and conflictual human-human and human-animal interactions
– are highly relevant. Both of them are attentionally critical (as revealed by higher
P300 for both HH and HA) but the negative
situations seemed to be able to
elicit an increased emotional response when subjects observ
ed aggressive HA
interactions. This may be due to the pote
ntial lack of control on the situation
which the subject has to face: in case of HA scenes, the unpredictable outcomes
of aggressive inter-species interactions
may be evaluated as more dangerous than
those of intra-species ones.
In addition, the role of the empathic
profile was found to be relevant, as
confirmed mainly by BEES measure. In fa
ct the emotional response mirrored by
the N300 deflection was greater in high- with respec
t to low-empathy
individuals. Thus, this pattern of response
s confirms the direct link between trait
empathy and brain responses. However this trait-modulation was not generic but
context- and valence-related. Indeed this result was obtained only in response to
negative situations in the case of both HH and HA interaction scenes, and highly
empathic and lowly empathic participants
did not differ in terms of “emotional
resonance” in positive or neutral situat
ions. That is, the aggressive situations
elicited a consistent and intense response in highly empathic subjects when a
human is threatened independently from the eliciting context (HH and HA).
In contrast, no significant associatio
n was found between trait empathy and
P300 ERP deflection. The reason why th
e P300 modulation was not directly
related to empathic trait is presumably
linked to the functional (cognitive and
attentional) significance of this ERP defl
ection, without a specific relation with
the emotional valence per se, but to the re
levance of the situations. Moreover, the
absence of significant correlations be
tween ERPs and IRI measures may be
explained by considering the limited sensit
ivity of this measure in respect to the
emotional content of the empathic situ
ations as compared to the BEES. IRI
indeed more specifically tests “cogniti
ve” empathic components and includes
heterogeneous elements, such as cognitive
perspective-taking or personal distress.
Future research should better explore this issue, for example by directly
comparing and investigating the relative
role of different components of the
empathy construct (e.g. emotional or cognitive ones).
To summarize, our results highlight the potential of using
psychophysiological and personality indi
ces to measure emotional empathy in
contexts with different biological and evolutionary meanings, involving species-
specific and species-aspecific relationships (Balconi
& Canavesio, 2013a, 2013b;
Carlo, Hausmann, Christiansen, & Randall, 2003; Chiu Loke, Evans, & Lee,
2011). Moreover, brain activity was analysed
to investigate markers of affective
processes supporting emotional “resonance
mechanisms” that are activated when
we face an emotionally-connoted si
tuation (Balconi & Bortolotti, 2012a). These
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mechanisms may be plausibly considered
as relatively independent from the
actors involved in an interaction (i.e. would they be only humans or humans and
animals), as they may be considered phylogenetically and evolutionary acquired
to respond to emotional situations where at least a consimilar is implicated.
Nonetheless, P300 component proved to be
sensitive to the species condition,
since it signalled the relevance of HA in
teractions when a negative context was
considered. According to the role of this kind of stimuli in eliciting uncontrolled,
primitive and orienting responses, significant higher respon
ses emerged in the
case of dog/cat attacks toward humans.
Finally, psychophysiological indices differed depending on individual
empathy traits. High-empathy participan
ts, as compared to their low-empathy
counterparts, exhibited greater brain resp
onsiveness to emotional situations for
both species-specific and species-aspecific interactions.
However, an ampler sample should be used to make the main effects we
found more robust. As for ERPs significance, the roles of
the N300 component
and of a possible anticipated N250 deflection should be distinguished. Indeed
species-specific and species-aspecific relationships require an emotional
component and recent observations un
derlined that N250 amplitude might
mirror the increased effort in attributing
emotions to inanimate objects. Due to
the latency feature in the present paper we may not totally exclude the
possibility that the observed negati
ve deflection could be a later N250
phenomenon. However the cortical locali
zation and the latency values (later
than 300 msec) could suggest a later
than early deflection. Finally, the
familiarity with animal interactions ma
y be taken in consideration to better
elucidate the effect that previous rela
tionships with other species has on the
emotional response to inter-species contexts.
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